performance analytics

Whether you're a DBA, data scientist or developer, you're probably considering how the cloud can help modernize your information management and analytics strategy. Cloud data warehousing can help you get more value from your data by combining the benefits of the cloud - speed, scale, and agility - with the simplicity and performance of traditional on-premises appliances.
This white paper explores how a cloud data warehouse like IBM dashDB can reduce costs and deliver new business insights. Readers will learn about:
- How data warehousing-as-a-service helps you scale without incurring extra costs
- The benefits of in-database analytics in a cloud data warehouse
- How a cloud data warehouse can integrate with the larger ecosystem of business intelligence tools, both on prem and off prem

Enterprises are focusing on becoming ever more data-driven, meaning that it is simply unacceptable to allow data to go to waste. Yet, as the amount of data businesses collect and control continues to increase exponentially, many organizations are failing to derive enough business value from their data. Companies are feeling the pressure to extract maximum value from all of their data, both defensive and offensive. Defensive analytics are the “plumbing aspects” of data management that must be captured to mitigate risk and establish a basic understanding of business performance. Offensive analytics build on defensive analytics and support overarching business objectives, strategic initiatives and long-term goals using predictive models. In this whitepaper, you will learn how to address many challenges, including streamlining operational reporting, delivering insight and providing a single, unified platform for everyone.

People analytics is increasingly on the agenda for organisations. With the rise of workplace technology allowing leaders to track employees’ performance, productivity and wellbeing, we partnered with the CIPD to survey over 3,000 business professionals to understand how people analytics is being used.
And the results are in. 65% of respondents who work in an organisation with a strong people analytics culture, say their business performance is strong compared to competitors.
As well as outlining the key opportunities leaders can capitalise on, this report covers:
- How different professions are using people data
- The various types of people data that are being used
- How people analytics adds value to organisations
- What the future holds for people data

Digital transformation is poised to change the supply chain more
profoundly than any other functional area and more dramatically than at
any point in its history in terms of driving efficiency and resiliency to
disruption. In the context of the challenges facing supply chains, both now
and in the future, it becomes clear that the old ways of working will not
suffice and that even best-in-class performance today is unlikely to be good
enough in the future. It is the view of IDC that the supply chain must
become a "thinking" supply chain, one that is intimately connected to all
data sources, enabled with comprehensive and fast analytics, openly
collaborative through cloud-based commerce networks, conscious of
cyberthreats, and cognitively interwoven. According to IDC supply chain research, technology is emerging as a prime
driver of change, particularly artificial intelligence, blockchain, and the Internet of Things (IoT).

This white paper examines the true costs associated with the Tagging of websites to implement and track the performance of online marketing technologies such as web analytics, display ad serving and search marketing. This research was conducted by TagMan, a smart container tag with real-time attribution and web-page acceleration.

Ignoring the potential of AR analytics is a losing game. In order to boost your collection rate and maximize resources, departments should be analyzing a plethora of statistics — not just DSO.
This playbook discusses the six metrics your AR department should be paying attention to and how they can separate themselves from competition and provide customers with an improved experience by:
• Measuring Key Performance Indicators (KPIs)
• Making process improvements based on analytics
• Centralizing collection activities

In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.

"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out:
Top 5 causes of downtime and poor performance across the infrastructure stack
How machine learning and predictive analytics can prevent issues
Steps you can take to boost performance and availability"

There is a lot of industry buzz about Key Performance Indicators (KPIs), but most contact centers currently focus on only one or two core KPIs, such as “Service Level,” and are only equipped to optimize these KPIs locally. Few contact centers have the tools to manage performance globally.

Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time.
AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance.
In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences.
Join this webinar to learn:
How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development.
How AWS supports BI solutions f

Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight.
This ESG report highlights:
• Optimal application performance and delivery is difficult to achieve in complex environments.
• Many IT infrastructure and operations teams are stretched to the breaking point.
• Predictive analytics and machine learning can be applied to great effect.

"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out:
-Top 5 causes of downtime and poor performance across the infrastructure stack
-How machine learning and predictive analytics can prevent issues
-Steps you can take to boost performance and availability

Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better

Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business,
mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and
enough compute power to deliver the performance required in a rapidly evolving digital marketplace.
Customers increasingly drive the speed of business, and organizations need to engage with customers
on their terms. The need to manage sensitive information with high levels of security as well as
capture, analyze, and act upon massive volumes of data every hour of every day has become critical.
These challenges will dramatically change the way that IT systems are designed, funded, and run
compared to the past few decades. Databases and Java have become the de facto language in which
modern, cloud-ready applications are written. The massive explosion in the volume, variety, and
velocity of data increases the need for secure and effective analytics so that organizations can make
better

Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been
top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar
database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as
quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data
from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure
1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP
database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks
can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data.
In-memory databases have helped address p

To stay ahead in today's hybrid network, you need a lens into the end user's experience as well as an understanding of the dependencies between your applications and network. With this approach, you are alerted to issues before the business is impacted and problems are resolved faster. This eBook details what you need to know to select a best of breed network performance management solution and outlines the critical capabilities required for deep application visibility across virtualized, hybrid and cloud networks no matter where a user is located. Read this book and:
Discover best practices - for proactive network monitoring and fast troubleshooting
Learn how to stay ahead of application performance issues with increased visibility
Increase productivity and a higher ROI - with automatic discovery, end-to-end monitoring, reporting, analytics and faster MTTR
Ensure your approach is a proactive mode
Study the

Read this to find out how we developed a decision-support tool to help a major transport operator use data and analytics to optimise commercial performance. Discover:
what happens when humans are faced with complex decisions
how data and analytics can be applied to improve decision making
how a decision-support tool works in real life (video)
what lessons your business can learn from this case story.

People analytics is increasingly on the agenda for organisations. With the rise of workplace technology allowing leaders to track employees’ performance, productivity and wellbeing, we partnered with the CIPD to survey over 3,000 business professionals to understand how people analytics is being used.
And the results are in. 65% of respondents who work in an organisation with a strong people analytics culture, say their business performance is strong compared to competitors.
As well as outlining the key opportunities leaders can capitalise on, this report covers:
- How different professions are using people data
- The various types of people data that are being used
- How people analytics adds value to organisations
- What the future holds for people data

Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202

The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics.
To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.

Malicious botnets present multiple challenges to enterprises — some threaten security, and others merely impact performance or web analytics. A growing concern in the bot environment is the practice of credential stuffing, which capitalizes on both a bot’s ability to automate repeat attempts and the growing number of online accounts held by a single user. As bot technologies have evolved, so have their methods of evading detection. This report explains how the credential stuffing exploit challenges typical bot management strategies, and calls for a more comprehensive approach.

Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry
The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments.
By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models.
View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.

"We will show you the power of the ServiceNow single system of record through some easy-to-follow demonstrations. This webinar includes demonstrations of:
• Incident, Problem and Change Management
• Service Catalog & Self Service
• Performance Analytics "

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